Analysis of the allergenic proteins in black tiger prawn ( <i>Penaeus monodon</i> ) and characterization of the major allergen tropomyosin using mass spectrometry
Bibliographic record
Abstract
Crustaceans are the third most prevalent cause of food-induced anaphylaxis after peanuts and tree nuts. The severity of the allergenic proteins depends mainly on the amino acid sequence that induces production of IgE antibodies. In black tiger prawn (Penaeus monodon), the crude protein extract was profiled and its allergenic potency was examined against patient's sera. Proteins having strong immunoreactivity with patient's IgE were characterized using peptide mass fingerprinting (PMF). Tropomyosin (TM) (33 kDa), myosin light chain (20 kDa), and arginine kinase (40 kDa) were identified as allergenic proteins. Tropomyosin, the most abundant and potent allergen, was purified using ion-exchange chromatography for de novo sequencing experiments. Using bottom up tandem mass spectrometry, the full amino acid sequence was achieved by a combination of matrix-assisted laser desorption/ionization (MALDI) and electrospray ionization (ESI) tandem mass spectrometry (QqToF). Myosin light chain and arginine kinase were also characterized, and their related peptides were de novo sequenced using the same approach. The immunological reactivity of the crude prawn extracts and purified TM samples were analyzed using a large number of patients' sera. A signature peptide was assigned for the TM protein for future quantification work of black tiger prawn TM levels in different matrices (i.e. water, air, food) in the seafood industry.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".